Abstract
Now people are using the network all the time, but the ensuing network attacks are constantly threatening people’s lives, so information security is becoming more and more important. In this paper, an intrusion detection model based on the MEA-Elman neural network is proposed. Firstly, GA algorithm is used to reduce the dimension of the dataset, and then verified by the MEA-Elman network model. The experiment results show that the detection model has high accuracy, which can meet the basic requirements of intrusion detection.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Aminanto, E.M., Kim, K.: Deep learning in intrusion detection system: an overview. In: International Research Conference on Engineering and Technology (2016)
Yang, Y., Huang, H.: Research on intrusion detection based on incremental GHSOM. Chin. J. Comput. 37(5), 1216–1224 (2014)
Aditya Shrivastava, M.B., Gupta, H.: A novel hybrid feature selection and intrusion detection based on PCNN and support vector machine. Comput. Technol. Appl. 4, 922–927 (2013)
Gautam, S.K., Om, H.: Computational neural network regression model for host based intrusion detection system. Perspect. Sci. 8, 93–95 (2016)
El Farissi, I., Saber, M., Chadli, S., Emharraf, M., Belkasmi, M.G.: The analysis performance of an intrusion detection systems based on neural network
Kosek, A.M., Gehrke, O.: Ensemble regression model-based anomaly detection for cyber-physical intrusion detection in smart grids. In: 2016 IEEE Electrical Power and Energy Conference (EPEC) (2016)
Sasanka Potluri, C.D.: Accelerated deep neural networks for enhanced intrusion detection system (2016)
Tang, J., Cao, Y., Xiao, J., et al.: Predication of plasma concentration of remifentanil based on Elman neural network. J. Central South Univ. 20(11), 3187–3192 (2013)
Zhang, Q., Xu, Z., Zhao, K.: Prediction of data from pollution sources based on Elman neural network. J. South Chin. Univ. Technol. (Nat. Sci. Edn.) 37(5), 135–138 (2009)
Chengyi, S., Keming, X., Mingqi, C.: Mind-evolution-based machine learning framework and new development. J. Taiyuan Univ. Technol. 5, 453–457 (1999)
Karegowda, A.G., Jayaram, M.A., Manjunath, A.S., et al.: GA based Dimension Reduction for enhancing performance of k-means and fuzzy k-means: a case study for categorization of medical dataset. Adv. Intell. Syst. Comput. 201, 169–180 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Zhang, Z., Zhang, G., Shen, Y., Zhu, Y. (2019). Intrusion Detection Model Based on GA Dimension Reduction and MEA-Elman Neural Network. In: Barolli, L., Xhafa, F., Javaid, N., Enokido, T. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2018. Advances in Intelligent Systems and Computing, vol 773. Springer, Cham. https://doi.org/10.1007/978-3-319-93554-6_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-93554-6_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93553-9
Online ISBN: 978-3-319-93554-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)